prompt_fine_tuned_CB_XLMroberta

.gitattributes

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+tokenizer.json filter=lfs diff=lfs merge=lfs -text

README.md

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+---
+license: mit
+library_name: peft
+tags:
+- generated_from_trainer
+base_model: xlm-roberta-base
+metrics:
+- accuracy
+- f1
+model-index:
+- name: prompt_fine_tuned_CB_XLMroberta
+  results: []
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# prompt_fine_tuned_CB_XLMroberta
+
+This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.4733
+- Accuracy: 0.3182
+- F1: 0.1536
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 2e-05
+- train_batch_size: 1
+- eval_batch_size: 1
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- training_steps: 400
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss | Accuracy | F1     |
+|:-------------:|:------:|:----:|:---------------:|:--------:|:------:|
+| 0.9542        | 0.4545 | 50   | 1.1060          | 0.3182   | 0.1536 |
+| 0.8627        | 0.9091 | 100  | 1.1621          | 0.3182   | 0.1536 |
+| 0.6647        | 1.3636 | 150  | 1.2304          | 0.3182   | 0.1536 |
+| 0.8065        | 1.8182 | 200  | 1.3215          | 0.3182   | 0.1536 |
+| 0.7675        | 2.2727 | 250  | 1.3718          | 0.3182   | 0.1536 |
+| 0.8203        | 2.7273 | 300  | 1.4238          | 0.3182   | 0.1536 |
+| 0.7817        | 3.1818 | 350  | 1.4576          | 0.3182   | 0.1536 |
+| 0.7012        | 3.6364 | 400  | 1.4733          | 0.3182   | 0.1536 |
+
+
+### Framework versions
+
+- PEFT 0.11.1
+- Transformers 4.40.2
+- Pytorch 2.2.1+cu121
+- Datasets 2.19.1
+- Tokenizers 0.19.1

adapter_config.json

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+{
+  "auto_mapping": null,
+  "base_model_name_or_path": "xlm-roberta-base",
+  "inference_mode": true,
+  "num_attention_heads": 12,
+  "num_layers": 6,
+  "num_transformer_submodules": 1,
+  "num_virtual_tokens": 12,
+  "peft_type": "PROMPT_TUNING",
+  "prompt_tuning_init": "RANDOM",
+  "prompt_tuning_init_text": null,
+  "revision": null,
+  "task_type": "SEQ_CLS",
+  "token_dim": 768,
+  "tokenizer_kwargs": null,
+  "tokenizer_name_or_path": "xlm-roberta-base"
+}

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runs/May20_08-15-06_8e4208ae99b7/events.out.tfevents.1716192906.8e4208ae99b7.174.0

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tokenizer_config.json

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